The autonomic response following taVNS predicts changes in level of consciousness in DoC patients
Abstract
Abstract Advancements in emergency medicine and critical care have significantly improved survival rates for patients with severe acquired brain injuries(sABI), subsequently increasing the prevalence of disorders of consciousness (DoC) such as Unresponsive Wakefulness Syndrome (UWS) and Minimally Conscious State (MCS). However, the assessment of conscious states relies on the observation of behavioral responses, the interpretation of which may vary from evaluator to evaluator, as well as the high rate of misdiagnosis, which together pose significant challenges for clinical diagnosis. The study investigates the utility of transcutaneous auricular vagus nerve stimulation (taVNS) in modulating autonomic responses, as evidenced through heart rate variability (HRV), for distinguishing between healthy individuals and DoC patients and for prognosticating patient outcomes. A prospective randomized clinical trial was conducted from Februry 9, 2022, to February 4, 2024, at Hangzhou Armed Police Hospital in China. Healthy controls (HC) and DoC patients were enrolled in this study. The taVNS was administered to each subject for ten minutes. There electrocardiogram (ECG) signals were recorded for the analysis of HRV both during the stimulation and the ten minutes of rest that preceded and followed the stimulation. Subsequent investigations utilized Support Vector Machine (SVM) modeling, enhanced by a Radial Basis Function (RBF) kernel, to explore potential predictors of patient outcomes. This approach aimed to differentiate HC from DoC and MCS from UWS patients. 26 HC and 36 patients diagnosed with DoC were included in the analysis,. The DoC group consisted of 17 patients with a diagnosis of MCS and 19 with diagnosis of UWS/VS. Significant modulations in HRV parameters (HF, VLF, SampEn) were observed, indicating variations in autonomic response between the control group and DoC patients. Using the VLF, LF, and SampEn features in SVM model, DoC and HC were correctly classified with an accuracy of 86%. Similarly, MCS and UWS were classified with an accuracy of 78%. The SVM modeling achieved an 86% accuracy rate in predicting outcomes three months post-intervention, with a 71% confirmation rate at six months.The results highlight taVNS’s potential as a therapeutic modality in managing DoC by demonstrating its impact on autonomic regulation and suggesting pathways for enhancing recovery, which accentuates the significance of exploring brain-heart dynamics in DoC, presenting a novel approach to therapeutic strategies. Trial Registration Information: URL: chictr.org.cn; Unique identifier: ChiCTR2100045161. Date of the first registration: 9th/ April/ 2021.
Article Details
Authors (18)
Yan Li
Francesco Riganello
Jing Yu
Institute for Digital Molecular Analytics and Science (IDMxS), Nanyang Technological University, 59 Nanyang Drive, Singapore 636921, Singapore
Martina Vatrano
Mingquan Shen
Lijuan Cheng
Xiaohua Hu
State Key Laboratory of Marine Environmental Science, Xiamen University
Chengcheng Ni
Feiyang Wang
Bo Zheng
Chengcheng Zhang
State Key Laboratory of Coordination Chemistry, Collaborative Innovation Center of Advanced Microstructures, School of Chemistry and Chemical Engineering
Chaoyi Xie
Meiqi Li
State Key Laboratory of Green Papermaking and Resource Recycling, National Observation and Research Station of Erhai Lake Ecosystem in Yunnan, Yunnan Dali Research Institute, School of Environmental Science and Engineering
Wangshan Huang
Fangfang Shou
Nantu Hu
Steven Laureys
Haibo Di